SubCom analysis: a subcommunity-based workflow to infer taxon-specific contributions and microbial interactions (microbiomejournal.biomedcentral.com)

• SubCom analysis uses 558 randomly assembled low-complexity subcommunities and decision-tree models to predict community function from composition.
• Models identified Pseudomonas and Acinetobacter as positive contributors to aniline degradation, while Achromobacter had negative association despite expected role.
• Augmentation assays validated model predictions and enabled targeted enhancement of community function.

"Researchers developed SubCom analysis, an experimental-computational workflow that uses randomly assembled low-complexity subcommunities and decision-tree models to infer taxon-specific contributions and interaction contexts in microbial communities. Applied to an aniline-degrading community with 558 subcommunities, the models identified Pseudomonas and Acinetobacter as positive contributors to aniline utilization and Achromobacter as negative, despite its expected role. The models also indicated attenuation of positive effects by Corynebacterium. Augmentation assays validated predictions and enabled targeted community improvement."